Data Engineer -IT
Pubblicato il 19-08-2026 - Credit Research Initiative (CRI) in Ville Sur Nus
The Credit Research Initiative (CRI) team is a world leader in studying and applying the modern data analytics and conventional economic/financial models to credit risk analysis. D. candidates/holders from quantitative disciplines to apply for the Research Fellowship. It was launched after the 2008-2009 financial crisis and premised upon the concept of credit ratings as a public good.
Over the course of its developments, it has produced top-tier original research and has helped a wide range of financial institutions, supranational organizations and FinTech companies to solve real-world problems. In collaboration with the International Monetary Fund (IMF), the CRI has developed an automated stress-testing tool based on the CRI PD system - the Bottom-up Default Analysis (BuDA) toolkit. Together with a Singapore-based FinTech company, our technology is extended to help build its credit rating system for Small and Medium-sized Enterprises (SMEs).
The CRI team joins the Asian Institute of Digital Finance in NUS in 2020 and currently actively pursues a research project on Natural Language Processing (NLP) to extract credit-focused sentiments in media to complement the structured financial and behavioural data. Looking into the future, the CRI will continue to make the most of data analytics,
further automate the system and make the products more actionable for various users.
Responsibilities (include But Not Limited To) Conducting individual research for journal publications on credit risk management, data analytics, natural language processing, machine learning, deep learning, financial modelling, finance/economics empirical analyses, algorithm development, databases, etc.Participating in the CRI operations in terms of model development/validation, data production, system enhancement and knowledge dissemination.Participating in the consulting projects for external parties (e.g. bespoke model development/validation). D. degree from a quantitative discipline, e.g.
Computer
Science, Mathematics, Statistics, Physics, Engineering, Operations Research, Marketing, Economics, Finance, etc. D. degree at the time of appointment.Intending to do good research and striving to have a real-world impact.Strong team spirit and comfortable working with a diverse team in a multi-cultural environment.Responsible and resilient when faced with challenges.NUS Personal Data Consent for Job Applicants;A statement of future research plan and samples of research work;Two reference letters. #